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撤回文章:饮食代谢型建模可预测个体对饮食干预的反应。

RETRACTED ARTICLE: Dietary metabotype modelling predicts individual responses to dietary interventions.

作者信息

Garcia-Perez Isabel, Posma Joram M, Chambers Edward S, Mathers John C, Draper John, Beckmann Manfred, Nicholson Jeremy K, Holmes Elaine, Frost Gary

机构信息

Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.

Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.

出版信息

Nat Food. 2020 Jun;1(6):355-364. doi: 10.1038/s43016-020-0092-z. Epub 2020 Jun 17.

Abstract

Habitual consumption of poor quality diets is linked directly to risk factors for many non-communicable diseases. This has resulted in the vast majority of countries and the World Health Organization developing policies for healthy eating to reduce the prevalence of non-communicable diseases in the population. However, there is mounting evidence of variability in individual metabolic responses to any dietary intervention. We have developed a method for applying a pipeline for understanding interindividual differences in response to diet, based on coupling data from highly controlled dietary studies with deep metabolic phenotyping. In this feasibility study, we create an individual Dietary Metabotype Score (DMS) that embodies interindividual variability in dietary response and captures consequent dynamic changes in concentrations of urinary metabolites. We find an inverse relationship between the DMS and blood glucose concentration. There is also a relationship between the DMS and urinary metabolic energy loss. Furthermore, we use a metabolic entropy approach to visualize individual and collective responses to dietary interventions. Potentially, the DMS offers a method to target and to enhance dietary response at the individual level, thereby reducing the burden of non-communicable diseases at the population level.

摘要

长期食用低质量饮食直接与多种非传染性疾病的风险因素相关。这导致绝大多数国家和世界卫生组织制定了健康饮食政策,以降低人群中非传染性疾病的患病率。然而,越来越多的证据表明,个体对任何饮食干预的代谢反应存在差异。我们开发了一种方法,通过将高度受控饮食研究的数据与深度代谢表型分析相结合,应用一个流程来理解个体对饮食反应的差异。在这项可行性研究中,我们创建了一个个体饮食代谢型评分(DMS),该评分体现了个体饮食反应的差异,并捕捉了尿代谢物浓度随之而来的动态变化。我们发现DMS与血糖浓度之间存在负相关关系。DMS与尿代谢能量损失之间也存在关系。此外,我们使用代谢熵方法来可视化个体和集体对饮食干预的反应。DMS有可能提供一种在个体层面上针对并增强饮食反应的方法,从而在人群层面上减轻非传染性疾病的负担。

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